25 January 2018 Detection of damaged areas caused by the oil extraction in a steppe region using winter landsat imagery
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Abstract
Oil production in a steppe region disturbs the landscape and damages the steppe ecosystem. The objective of this research was to detect areas damaged by oil production in an oil field within the Russian Volga–Ural steppe region using winter Landsat imagery. We developed a practicable and effective approach using winter snow season multispectral Landsat satellite imagery. To this end, we applied seven algorithms of spectral or texture-based transformation: K-means, maximum likelihood estimation, topsoil grain size index, soil brightness, normalized differential snow index, tasselled cap, and co-occurrence measures. The co-occurrence texture measure variance shows the optimal result of identifying damaged areas. The unique feature of our method is that it can differentiate damaged areas from the bare soil of cropland within a cold steppe region where the area damaged by oil production is mixed with bare (fallow) croplands that have a polygonal shape similar to well pads. Such similarities can lead to confusion in object-based classification. Using the co-occurrence measures, we found that from 1988 to 2015, damaged area is nearly three times as big in the peak period of the oil field development (2001 and 2009) as in 1988. Landscape fragmentation also peaked in 2001 and 2009. Our approach for this project is useful and cost effective regular monitoring of damages from oil production for both the Volga–Ural steppe region and other cold steppe regions.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Ksenya Mjachina, Ksenya Mjachina, Zhiyong Hu, Zhiyong Hu, Alexander Chibilyev, Alexander Chibilyev, } "Detection of damaged areas caused by the oil extraction in a steppe region using winter landsat imagery," Journal of Applied Remote Sensing 12(1), 016017 (25 January 2018). https://doi.org/10.1117/1.JRS.12.016017 . Submission: Received: 7 August 2017; Accepted: 26 December 2017
Received: 7 August 2017; Accepted: 26 December 2017; Published: 25 January 2018
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